Sentinel-1 for High Resolution monitoring of vegetation Dynamics

01.12.2018 - 30.11.2021
Research funding project

The objective of this study is to develop and use a novel high-resolution vegetation optical depth dataset based on ESA’s Sentinel-1 satellites to improve our understanding on the local impacts of water availability on vegetation at a global scale using novel machine learning approaches. We will use Copernicus Sentinel-1 in combination with MetOp ASCAT VOD to 1) establish quantitative relationships between Sentinel-1 backscatter and ratios thereof and MetOp ASCAT VOD, to then 2) develop a high-resolution 1 km VOD product sensitive to changes in water content of the above ground biomass. The newly developed VOD will be 3) evaluated using different ESA and non-ESA EO datasets, among which are CGLS LAI and ESA’s Earth Explorer SMOS VOD. Finally the high-resolution VOD will be used to 4) quantify the effect of water availability on vegetation dynamics for different land cover types at the local scale.

People

Project leader

Project personnel

Institute

Grant funds

  • ESA / ESTEC (EU) European Space Agency (ESA) Call identifier Living Planed Fellowship Specific program Living Planed Fellowship

Research focus

  • Environmental Monitoring and Climate Adaptation: 100%

Keywords

GermanEnglish
Sentinel 1Sentinel 1
Wasserverfügbarkeitwater availability
Machine learningMachine learning
Vegetationvegetation

Publications